China is a key region for understanding fire activity and the drivers of its variability under strict fire suppression policies. Here, we present a detailed fire occurrence dataset for China, the Wildfire Atlas of China (WFAC; 2005–2018), based on continuous monitoring from multiple satellites and calibrated against field observations. We find that wildfires across China mostly occur in the winter season from January to April and those fire occurrences generally show a decreasing trend after reaching a peak in 2007. Most wildfires (84%) occur in subtropical China, with two distinct clusters in its southwestern and southeastern parts. In southeastern China, wildfires are mainly promoted by low precipitation and high diurnal temperature ranges, the combination of which dries out plant tissue and fuel. In southwestern China, wildfires are mainly promoted by warm conditions that enhance evaporation from litter and dormant plant tissues. We further find a fire occurrence dipole between southwestern and southeastern China that is modulated by the El Niño-Southern Oscillation (ENSO).

Purpose This paper aims to develop a coordination mechanism that can be applied to achieve the channel coordination and information sharing simultaneously in the fresh agri-food supply chain with uncertain demand. It seeks to elucidate how the producer can use an option contract to transfer the risk caused by uncertain demand, impel the retailer to share demand information and improve the performance of supply chain. Design/methodology/approach An option contract model based on the basic model of fresh agri-food supply chain is introduced to compare the production, profit, risk and information sharing condition of the supply chain in different cases. In addition, a case study focusing on the sale of autumn peaches produced by a local producer is investigated, which provides evidence of the applicability of the authors’ approach. Findings The optimal option contract can help the supply chain achieve channel coordination and reach Pareto improvement. In the meantime, such a contract will encourage the retailer to share market demand information with producer spontaneously and help maintain the strategic cooperation between two parties. Research limitations/implications This paper considers a single-producer, single-retailer system and both of them are risk neutral. Practical implications Presented results can be used as suggestions for improving the contract design of fresh agri-food supply chain in China and can also provide references for other countries with similar experiences as China in fresh agri-food production. Originality/value This research introduces the option contract into fresh agri-food supply chain and takes information sharing and the risk caused by uncertain demand into consideration.

Logistics demand forecasting is important for investment decision-making of infrastructure and strategy programming of the logistics industry. In this paper, a hybrid method which combines the Grey Model, artificial neural networks and other techniques in both learning and analyzing phases is proposed to improve the precision and reliability of forecasting. After establishing a learning model GNNM(1,8) for road logistics demand forecasting, we chose road freight volume as target value and other economic indicators, i.e. GDP, production value of primary industry, total industrial output value, outcomes of tertiary industry, retail sale of social consumer goods, disposable personal income, and total foreign trade value as the seven key influencing factors for logistics demand. Actual data sequences of the province of Zhejiang from years 1986 to 2008 were collected as training and test-proof samples. By comparing the forecasting results, it turns out that GNNM(1,8) is an a ppropriate forecasting method to yield higher accuracy and lower mean absolute percentage errors than other individual models for short-term logistics demand forecasting

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Abstract. Consider a supply chain consisting of a retailer and a supplier, and the yield of the supplier is random while the market demand of the retailer is stochastic. Due to the double marginalization, the wholesale price contract can't achieve the coordination of the supply chain, we introduce option contracts into the supply chain in order to investigate whether option contracts can improve the supply chain's performance under the circumstance where the yield and demand are all uncertain. Through establishing the dynamic Stackelberg game model, which is dominant by the retailer, we discuss the optimal production strategy of the supplier and the optimal purchasing strategy of the retailer, find that the relationship between the production input and the option order quantity is non-linear. In addition, sensitivity analysis indicate that the correlations of decision variables with several parameters. Researches show that option contracts not only offering flexibility for retailer's purchasing, it can also achieve supply chain coordination under some certain conditions.